On average across the 29 countries covered, the share of jobs at potential high risk of automation is around 3 per cent by the early 2020s, but this rises to almost 20 per cent by the late 2020s, and 30 per cent by the mid-2030s.

PwC notes New Zealand will fare better because of the country’s higher concentration of jobs in industries with relatively low potential automation rates, rising to only 24 per cent by the mid-2030s.

“The data suggests New Zealand has the opportunity to continue creating jobs for people as the world navigates through the coming waves of automation,” says Andy Symons, innovation partner at PwC New Zealand.

“We have a workforce that’s built on roles that are less automatable on average than many countries around the world.

“That doesn’t mean we can be complacent though. Both businesses and government should be developing strategies around retraining options for workers and building an education system that allows us to replace jobs that are lost through automation.”

The report notes New Zealand is part of a small group of countries, along with the Nordic countries and Greece, where the workforce is concentrated in industries with relatively lower potential automation rates, and the roles workers hold are also on average less automatable.

“The report suggests we may experience a reduced impact relative to other countries,” says Symons. “We’re in good shape because of our economy’s focus on services, especially areas like tourism, which can’t be easily automated.”

But, he adds, “We still have to be looking at how we train our young people and reskill workers so they are ready to move into new roles that technology like AI will create.”

The three waves of automation

Between now and the mid-2030s, PwC expects three waves of automation to reshape the global economy.

The algorithm wave, which is already underway and involves automating structured data analysis and tasks, such as credit scoring. This wave will come to maturity by the early 2020s.

The augmentation wave is also underway and will mature later in the 2020s. The augmentation wave is focused on automating repeatable tasks, as well as the use of aerial drones, robots in warehouses and semi-autonomous vehicles.

In the third autonomy wave, which could come to maturity by the mid-2030s, AI will be able to analyse data, make decisions and take action with little or no human input. Fully autonomous driverless vehicles could roll out at scale in this phase, for example.

The table below summarises the estimates of the percentage of jobs that could be impacted over these three waves, both globally and in New Zealand.

PwC estimates of median values across 29 countries based on analysis of OECD PIAAC data

The research finds professionals, as well as senior officials and senior managers, are estimated to be at the lowest risk of automation throughout the three waves.

They are more likely to be engaged in social skills, literacy skills and more complex computational tasks that are less automatable. They also tend to be relatively highly educated and this will help them to adapt to new waves of technology so as to remain complementary to machines, rather than being replaced by them.

The nature of their work may change significantly over time like what happened with the advent of personal computers and then the internet. But they are less likely to find themselves displaced entirely by autonomous machines than a driver, factory worker or clerk.

The risk of automation cuts across age groups.

But despite the risks facing some young workers, they are potentially well positioned to capitalise on the new opportunities from digital technologies if they can acquire relevant training. Similarly, older workers also need to equip themselves with a skill set that complements the digital workplaces of future.

For both genders and across all age groups, highly educated workers consistently have lower automation risks in the long run. This reflects the fact that their roles involve skills of supervision and intellectual reasoning that will still be needed alongside AI-based systems.

Higher levels of education also allow workers flexibility to move around different occupations and industries and thus potentially escape automation risks, the report states.

Different worker types are impacted differently over time by successive automation waves – highly educated women performing clerical tasks and highly educated men in analytical jobs could, for example, be relatively vulnerable in the short-term.

The report says eventually, less educated men may face the highest risks as autonomous machines are deployed that can independently perform manual tasks such as driving, as well as many factory and warehouse jobs that currently employ a higher proportion of men than women.

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